[R-sig-ME] Removing random intercepts before random slopes

[Maarten Jung]

Dear list,

Does it make sense to remove random intercepts before one removes
random slopes (regarding the same grouping factor)?

Barr et al. (2013, [1]) suggest that a model "missing within-unit
random intercepts is preferable to one missing the critical random
slopes" (p. 276).
However, I wonder whether this procedure does make sense from a
conceptual perspective and whether it is reconcilable with the
principal of marginality?

And, is there any difference between LMMs with categorical and LMMs
with continuous predictors regarding this?

Best regards,
Maarten

[1] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3881361/